A Depth Learning-Based Approach for Vision Prevention and Detection Utilized on Mobile Devices
- DOI
- 10.2991/978-94-6463-370-2_38How to use a DOI?
- Keywords
- Visual Acuity Assessment; Image Processing; Deep Learning
- Abstract
Vision, one of humanity’s paramount senses, plays a pivotal role in our lives and learning. Maintaining a pair of healthy eyes is of utmost significance. Conventional vision assessments typically necessitate the expertise of ophthalmologists or optometrists to diagnose myopia. Unfortunately, this approach is fraught with substantial delays. Once myopia is confirmed post-refraction, the removal of eyeglasses becomes a formidable challenge. In recent years, the prevalence of myopia, especially among school-age children, has surged, resulting in a widespread reliance on corrective lenses.The imperative for vision preservation and safeguarding has never been more apparent. In light of the rapid advancements in computer vision and artificial intelligence technologies, this paper introduces an AI-based method, designed for deployment on mobile devices, for vision prevention and assessment. Integrating artificial intelligence image processing and pattern recognition techniques, this approach enables expeditious and precise evaluation of visual acuity through analysis of the subject’s ocular images. It presents a novel solution for ocular health maintenance and disease diagnosis.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yichuan Huang PY - 2024 DA - 2024/02/14 TI - A Depth Learning-Based Approach for Vision Prevention and Detection Utilized on Mobile Devices BT - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023) PB - Atlantis Press SP - 354 EP - 368 SN - 1951-6851 UR - https://doi.org/10.2991/978-94-6463-370-2_38 DO - 10.2991/978-94-6463-370-2_38 ID - Huang2024 ER -